Today, software developers or software providers strive continually to improve and refine their software products to remain competitive. On the other hand, with a significant number of software products available in market, it may be difficult for customers to choose a suitable software product. Therefore, for the software developers as well as for the customers investing in software, it is instrumental to know how users feel about the software product so that future directions in development and investment can be effective and easier.
Conventional methods of assessing feedback data of software products have significant disadvantages. For example, it is not clear which aspects of software are evaluated, so that often only the most obvious aspect (e.g., user interface (UI)) gets rated, while the software has many more qualities than the UI. Another fundamental shortcoming is the lack of correlation between the feedback data and level of global usage of the software. Further, the software developers could be able to submit a large number of high ratings, or feedback data with excessive or untrue praise, for their own software product. Hence, potential users or customers may find it difficult to determine whether or not reviewer ratings are meaningful, significant or even genuine.
Thereby the customers may find it difficult to determine the quality of the software product before viewing or using the software product, if the feedback data does not detail exactly which aspect of a software object has been evaluated, by whom the evaluation was performed, in which life-cycle phase of the software object an evaluation took place and so on. Further, the users may be required to manually research each potential review comment, read web forums and the like, corresponding to the software product and use their own judgment. Therefore, there is no systematic approach to valuate user feedback data on the software product and evaluate the software product based on the user feedback data.